All instance perception tasks aim at finding certain objects specified by some queries such
as category names, language expressions, and target annotations, but this complete field …

Abstract Referring Expression Segmentation (RES) aims to generate a segmentation mask
for the object described by a given language expression. Existing classic RES datasets and …

We design an open-vocabulary image segmentation model to organize an image into
meaningful regions indicated by arbitrary texts. Recent works (CLIP and ALIGN), despite …

Referring image segmentation aims to segment a referent via a natural linguistic expression.
Due to the distinct data properties between text and image, it is challenging for a network to …

Referring image segmentation is a fundamental vision-language task that aims to segment
out an object referred to by a natural language expression from an image. One of the key …

Parameter efficient tuning (PET) has received considerable attention owing to its
applicability to reduce the number of parameters that need to be updated while maintaining …

Referring image segmentation is an advanced semantic segmentation task where target is
not a predefined class but is described in natural language. Most of existing methods for this …

In this work, we address the challenging task of referring segmentation. The query
expression in referring segmentation typically indicates the target object by describing its …

We propose a Vision-Language Transformer (VLT) framework for referring segmentation to
facilitate deep interactions among multi-modal information and enhance the holistic …

In this paper, we propose a simple yet universal network termed SeqTR for visual grounding
tasks, eg, phrase localization, referring expression comprehension (REC) and segmentation …